Research on UAV Image Classification Based on Deep Learning

Runqi Li, Cen Chen, Mengyao Chen

Abstract

In order to improve the efficiency of urban traffic operation, this paper combines deep learning technology and UAV photography of drones. With the algorithm in this paper, we can classify traffic area and static area in high quality and speed. We make a test in Fengtai District of Beijing to conduct regional traffic identification research on the traffic content of the area. The primary identification area includes the vehicle travel area and coordinates the pedestrian area in a coordinated manner. The main research result of this algorithm is to propose a key frame extraction scheme for UAV image and then combine it with the application of Mask R-CNN in high-altitude image to identify the ground area. The experimental results are similar to the same algorithm (refer to FCNs for this article). Comparative benchmarks) have obvious advantages of high speed and high accuracy, which are of great help to traffic safety and urban planning.

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Paper Citation


in Harvard Style

Li R., Chen C. and Chen M. (2019). Research on UAV Image Classification Based on Deep Learning.In Proceedings of the International Conference on Advances in Computer Technology, Information Science and Communications - Volume 1: CTISC, ISBN 978-989-758-357-5, pages 148-152. DOI: 10.5220/0008098701480152


in Bibtex Style

@conference{ctisc19,
author={Runqi Li and Cen Chen and Mengyao Chen},
title={Research on UAV Image Classification Based on Deep Learning},
booktitle={Proceedings of the International Conference on Advances in Computer Technology, Information Science and Communications - Volume 1: CTISC,},
year={2019},
pages={148-152},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008098701480152},
isbn={978-989-758-357-5},
}


in EndNote Style

TY - CONF

JO - Proceedings of the International Conference on Advances in Computer Technology, Information Science and Communications - Volume 1: CTISC,
TI - Research on UAV Image Classification Based on Deep Learning
SN - 978-989-758-357-5
AU - Li R.
AU - Chen C.
AU - Chen M.
PY - 2019
SP - 148
EP - 152
DO - 10.5220/0008098701480152